Applications of Machine LearningLaajuus (5 cr)
Code: 5G00EV15
Credits
5 op
Objectives
The student is familiar with the most common algorithms and implementation techniques of machine learning. The student knows how to prepare the data, choose the method and teach the model. The student is able to control data driving in a learned model and analyze the results.
The student knows the principles of project management and management.
Content
Most common algorithms and implementation techniques for machine learning. Preparing data, selecting a method and teaching a model, driving data to a learned model, and analyzing the results.
Project management and management.
Assessment criteria, satisfactory (1-2)
The student is able to use a suitable machine learning method. Students get results using the model.
Assessment criteria, good (3-4)
The student is able to use a suitable method. The student is able to produce results using the model.
Assessment criteria, excellent (5)
The student is able to choose the most suitable method for the goal. The student is able to estimate the meaning of the results produced by the model.
Enrolment period
22.11.2023 - 05.01.2024
Timing
01.01.2024 - 05.05.2024
Credits
5 op
Mode of delivery
Contact teaching
Unit
ICT Engineering
Campus
TAMK Main Campus
Teaching languages
- Finnish
Degree programmes
- Degree Programme in ICT Engineering
Teachers
- Ossi Nykänen
Person in charge
Ossi Nykänen
Groups
-
21I224
Objectives (course unit)
The student is familiar with the most common algorithms and implementation techniques of machine learning. The student knows how to prepare the data, choose the method and teach the model. The student is able to control data driving in a learned model and analyze the results.
The student knows the principles of project management and management.
Content (course unit)
Most common algorithms and implementation techniques for machine learning. Preparing data, selecting a method and teaching a model, driving data to a learned model, and analyzing the results.
Project management and management.
Assessment criteria, satisfactory (1-2) (course unit)
The student is able to use a suitable machine learning method. Students get results using the model.
Assessment criteria, good (3-4) (course unit)
The student is able to use a suitable method. The student is able to produce results using the model.
Assessment criteria, excellent (5) (course unit)
The student is able to choose the most suitable method for the goal. The student is able to estimate the meaning of the results produced by the model.
Assessment scale
0-5
Enrolment period
15.12.2022 - 08.01.2023
Timing
01.01.2023 - 07.05.2023
Credits
5 op
Mode of delivery
Contact teaching
Unit
ICT Engineering
Campus
TAMK Main Campus
Teaching languages
- Finnish
Seats
0 - 50
Degree programmes
- Degree Programme in ICT Engineering
Teachers
- Ossi Nykänen
Person in charge
Ossi Nykänen
Groups
-
20I224
Objectives (course unit)
The student is familiar with the most common algorithms and implementation techniques of machine learning. The student knows how to prepare the data, choose the method and teach the model. The student is able to control data driving in a learned model and analyze the results.
The student knows the principles of project management and management.
Content (course unit)
Most common algorithms and implementation techniques for machine learning. Preparing data, selecting a method and teaching a model, driving data to a learned model, and analyzing the results.
Project management and management.
Assessment criteria, satisfactory (1-2) (course unit)
The student is able to use a suitable machine learning method. Students get results using the model.
Assessment criteria, good (3-4) (course unit)
The student is able to use a suitable method. The student is able to produce results using the model.
Assessment criteria, excellent (5) (course unit)
The student is able to choose the most suitable method for the goal. The student is able to estimate the meaning of the results produced by the model.
Assessment scale
0-5
Enrolment period
15.11.2021 - 09.01.2022
Timing
03.01.2022 - 01.05.2022
Credits
5 op
Mode of delivery
Contact teaching
Unit
ICT Engineering
Campus
TAMK Main Campus
Teaching languages
- Finnish
Degree programmes
- Degree Programme in ICT Engineering
Teachers
- Ossi Nykänen
Person in charge
Ossi Nykänen
Groups
-
19I224
Objectives (course unit)
The student is familiar with the most common algorithms and implementation techniques of machine learning. The student knows how to prepare the data, choose the method and teach the model. The student is able to control data driving in a learned model and analyze the results.
The student knows the principles of project management and management.
Content (course unit)
Most common algorithms and implementation techniques for machine learning. Preparing data, selecting a method and teaching a model, driving data to a learned model, and analyzing the results.
Project management and management.
Assessment criteria, satisfactory (1-2) (course unit)
The student is able to use a suitable machine learning method. Students get results using the model.
Assessment criteria, good (3-4) (course unit)
The student is able to use a suitable method. The student is able to produce results using the model.
Assessment criteria, excellent (5) (course unit)
The student is able to choose the most suitable method for the goal. The student is able to estimate the meaning of the results produced by the model.
Assessment scale
0-5